Μετάφραση και ανάλυση λέξεων από την τεχνητή νοημοσύνη ChatGPT
Σε αυτήν τη σελίδα μπορείτε να λάβετε μια λεπτομερή ανάλυση μιας λέξης ή μιας φράσης, η οποία δημιουργήθηκε χρησιμοποιώντας το ChatGPT, την καλύτερη τεχνολογία τεχνητής νοημοσύνης μέχρι σήμερα:
- πώς χρησιμοποιείται η λέξη
- συχνότητα χρήσης
- χρησιμοποιείται πιο συχνά στον προφορικό ή γραπτό λόγο
- επιλογές μετάφρασης λέξεων
- παραδείγματα χρήσης (πολλές φράσεις με μετάφραση)
- ετυμολογία
nested factorial - translation to ρωσικά
![Pareto plot]] showing the relative magnitude of the factor coefficients.](https://commons.wikimedia.org/wiki/Special:FilePath/Pareto plot filtration rate.svg?width=200 "Pareto plot]] showing the relative magnitude of the factor coefficients.")
математика
факторный эксперимент с группировкой
иерархический факторный эксперимент
![[[Relative error]] in a truncated Stirling series vs. number of terms](https://commons.wikimedia.org/wiki/Special:FilePath/Stirling series relative error.svg?width=200 "[[Relative error]] in a truncated Stirling series vs. number of terms")
![TI SR-50A]], a 1975 calculator with a factorial key (third row, center right)](https://commons.wikimedia.org/wiki/Special:FilePath/Vintage Texas Instruments Model SR-50A Handheld LED Electronic Calculator, Made in the USA, Price Was $109.50 in 1975 (8715012843).jpg?width=200 "TI SR-50A]], a 1975 calculator with a factorial key (third row, center right)")
2) факторный
Ορισμός
Βικιπαίδεια
In statistics, a full factorial experiment is an experiment whose design consists of two or more factors, each with discrete possible values or "levels", and whose experimental units take on all possible combinations of these levels across all such factors. A full factorial design may also be called a fully crossed design. Such an experiment allows the investigator to study the effect of each factor on the response variable, as well as the effects of interactions between factors on the response variable.
For the vast majority of factorial experiments, each factor has only two levels. For example, with two factors each taking two levels, a factorial experiment would have four treatment combinations in total, and is usually called a 2×2 factorial design. In such a design, the interaction between the variables is often the most important. This applies even to scenarios where a main effect and an interaction is present.
If the number of combinations in a full factorial design is too high to be logistically feasible, a fractional factorial design may be done, in which some of the possible combinations (usually at least half) are omitted.
